Tag Archives: Lambda Function

Amazon Web Services aka AWS provides many SaaS products.
In this post, I want to share my learnings and experiences while working on one of the SaaS Products called LAMBDA.

I’ll begin with explaining our use case a bit and then implementing and Deploying a Lambda.

USE CASE

I was working on designing and implementing on a requirement to ticket the Air Bookings. Without Ticketing, user cannot board a flight and thus fly.

MORE ABOUT TICKETING PROCESS

Ticketing is an orchestration of series of steps, some require Biz Logic evaluation and some require interacting with different 3rd Party Services multiple times over the network.

This process can be seen as event driven, can be done asynchronously with retry capabilities, scheduling capabilities, involving interaction with 3rd Party Services over the network.

It has to be completed within time constraints as per Airlines\GDSes otherwise user cannot fly.

After gathering requirements, it seems to be a usecase of building a BOT, a Ticketing Bot, more specifically and “Executor-Schedulor-Supervisor-Agent“ Pattern fitting very well technically.

WHAT IS “EXECUTOR-SCHEDULOR-SUPRVISOR-AGENT“?

It’s a Pattern where in roles and responsibilities are clearly separated out to different actors\components.
Executor, Supervisor, Agent represent different Blocks and each is responsible to perform clearly defined task.

Executor is responsible to execute the Orchestration and likewise for other. You may choose to use Persistent Workflow frameworks, Queues for orchestration execution.

WHERE DOES LAMBDA FIT IN OUR CASE?

Ticketing Process has to be completed for multiple bookings. After all, multiple users are doing bookings on our site.

This demands multiple executors to be running in parallel and executing an orchestration independently with no interference.

Obviously, you will want that each executor picks a different Booking for ticketing.
For this, you will have synchronization and other checks in place so that once booking is owned by any executor, it does not get executed by another Executor.

Let’s say, we have a strategy that once a booking is picked by an Executor, executor updates a workItem with it’s ownership, timestamp and changes it’s status to In_Progress to reflect that Ticketing Process has been kicked in.

Now think of a scenario where in

an executor(s) (Server) performing a ticketing process, crashes in the middle of the process.

Or, you want to deploy the incremental changes and that may involve halting\interrupting the currently executing Ticketing Processes.

The 3rd scenario can be dealt with publishing Events to reach to a consistent state and stop further processing.

But, what about other Scenarios ? In that, Ticketing Process(es) will appear to be running with In_Progress status while that’s not the case.

How will you ensure that those Processes get completed later?

We will for sure want to complete the Ticketing Process at any cost.

What if we have something which can detect such Stuck Bookings and reprocess them from the last checkpoint.

Lets just focus on Supervisor.

What is the role of “Supervisor”?

Supervisor is a component made responsible to detect such Stuck Bookings and queue them for further re-processing. Note that it does not start executing those processes, instead it just re-queues them so that an executor an pick it up again.

In our case, Supervisor has to connect to Queues\Data Stores hosted in VPC.
Ok. What are the other expectations from this Supervisor?

It has to be Available. You would not want your Supervisor to be down for a long time. However, you would want that when

A Single Supervisor can fulfill the need. No need to run the multiple Supervisors at a time.

Supervisor running periodically.

Supervisor running in background

Supervisor has no state attached to it

All the above expectations made LAMBDA a good Fit in our case.

Enough of the story 🙂 Before you start cursing me, let’s start building a Lambda.

LAMBDA

Lambda is a function that can be executed in AWS Cloud environment based on certain trigger policies. Trigger can be a scheduled timed event or S3 event or likewise.

Another problem, i have. I have different environments set up and in each environment, i have different settings, say mongodb cluster is different.
I want to package resource files in jar and load them as per environment rather than configuring each setting as an environment variable.

How can i initialize based on an environment?

Once again, AWS comes to a rescue. It provides an ability to specify environment variables while configuration and these environment variables get passed to Lambda Function as Environment Variables on each execution.
What if we set the Environment and based on it’s value we load the resource file like Spring loads the configuration based on Profile.

DEPLOYING LAMBDA

Using AWS CMD CLI (Command Line Interface) to upload jar and other required/optional configurations

Through AWS console where in you can provide different configurations

HOW CAN I\WE ACCOMPLISH THIS?

We use different environments like Test environment, Stress etc before releasing to PROD and in each environment, we want to have different settings. How can we pass different settings like we can activate different Profiles in Spring? [ANSWER]: AWS allows to configure and pass environment variables to a Lambda on execution. While configuring a Lambda Function, define what environment variables need to be passed to your Lambda and then based on those environment variables, do things.

Our Lambda needs to connect to components\services deployed in our VPC. On execution, Lambda function is not able to connect to that component. [ANSWER]: AWS considers and enforces Security . To allow connections, configure Lambda with proper SubnetIds of your VPCs and permissions.

Our Lambda is not Event driven. It’s based on files wriiten in S3. How can we pass event data to Lambda?[ANSWER]: This blog focussed on Lambda with no event data, however AWS supports different events. Refer AWS. In order to pass Event Data to Lambda Function, handler function can accept more parameters. Parameter can even be of Custom Type and AWS takes care of Serialization and De-serialization.

THINGS TO KEEP IN MIND

AWS puts restrictions on executing Lambda – be it a size of the jar or constraints on resources like cpu, memory etc. Always check restrictions on AWS Site before considering Lambda.

Make sure that you understand the billing. Lambda is billed based on resources usage and the total time for execution.

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